MODELING AND PERFORMANCE ANALYSIS FOR THE SERIAL AND PARALLEL PRODUCTION SYSTEM BASED ON GSPN

Differed from the existed applications of generalized stochastic Petri net(GSPN) theory in machine-tool manufacturing system, reliability computation of FMS, testabilityparameters determination and fault analysis, a new idea of applying GSPN to model and performanceanalysis for the serial and parallel production system is proposed. And one typical discrete eventdynamic system (DEDS), turner-unit of palletizing system, is taken as a real case to research. Basedupon the established GSPN models, the working performances of serial and parallel layout arecompared. Furthermore, their differences of working mechanisms including feeding mechanism,coordinating mechanism and monitoring mechanism are discussed. Thus the theoretical basis which ishelpful to appraise layout plan and its reasonableness is provided. Meanwhile, the research resultsshow that parallel layout is more advantageous to greatly improve the operational speed ofproduction system than serial one.

Performance evaluation of series and parallel strategies for financial time series forecasting

Background:Improving financial time series forecasting is one of the most challenging and vital issues facing numerous financial analysts and decision makers.Given its direct impact on related decisions,various attempts have been made to achieve more accurate and reliable forecasting results,of which the combining of individual models remains a widely applied approach.In general,individual models are combined under two main strategies:series and parallel.While it has been proven that these strategies can improve overall forecasting accuracy,the literature on time series forecasting remains vague on the choice of an appropriate strategy to generate a more accurate hybrid model.Methods:Therefore,this study’s key aim is to evaluate the performance of series and parallel strategies to determine a more accurate one.Results:Accordingly,the predictive capabilities of five hybrid models are constructed on the basis of series and parallel strategies compared with each other and with their base models to forecast stock price.To do so,autoregressive integrated moving average(ARIMA)and multilayer perceptrons(MLPs)are used to construct two series hybrid models,ARIMA-MLP and MLP-ARIMA,and three parallel hybrid models,simple average,linear regression,and genetic algorithm models.Conclusion:The empirical forecasting results for two benchmark datasets,that is,the closing of the Shenzhen Integrated Index(SZII)and that of Standard and Poor’s 500(S&P 500),indicate that although all hybrid models perform better than at least one of their individual components,the series combination strategy produces more accurate hybrid models for financial time series forecasting.

Local and parallel finite element algorithms for time-dependent convection-diffusion equations

Local and parallel finite element algorithms based on two-grid discretization for the time-dependent convection-diffusion equations are presented. These algorithms are motivated by the observation that, for a solution to the convection-diffusion problem, low frequency components can be approximated well by a relatively coarse grid and high frequency components can be computed on a fine grid by some local and parallel proce- dures. Hence, these local and parallel algorithms only involve one small original problem on the coarse mesh and some correction problems on the local fine grid. One technical tool for the analysis is the local a priori estimates that are also obtained. Some numerical examples are given to support our theoretical analvsis.

LOCAL AND PARALLEL FINITE ELEMENT ALGORITHMS FOR THE NAVIER-STOKES PROBLEM

Based on two-grid discretizations, in this paper, some new local and parallel finite element algorithms are proposed and analyzed for the stationary incompressible Navier- Stokes problem. These algorithms are motivated by the observation that for a solution to the Navier-Stokes problem, low frequency components can be approximated well by a relatively coarse grid and high frequency components can be computed on a fine grid by some local and parallel procedure. One major technical tool for the analysis is some local a priori error estimates that are also obtained in this paper for the finite element solutions on general shape-regular grids.

“Series and parallel” design of ether linkage and imidazolium cation synergistically regulated four-armed polymerized ionic liquid for all-solid-state polymer electrolyte

Developing all-solid-state polymer electrolytes(SPEs) with high electrochemical performances and stability is of great importance for exploiting of high energy density and safe batteries. Herein, ether linkage and imidazolium ionic liquid(ILs) are incorporated into the multi-armed polymer backbone though the series and parallel way. The parallel polymeric ionic liquid(P-P(PEGMA-IM)) maximizes the synergistic effect of ILs and ether linkage, which endowed the material with low crystallinity and high flame retardancy. The P-P(PEGMA-IM) based P-SPE presents a high ionic conductivity of 0.489 m S/cm at 60°C, an excellent lithium-ion transference number of 0.46 and a wide electrochemical window of 4.87 V.The assembled lithium metal battery using P-SPE can deliver a capacity of 151 m Ah/g at 0.2 C, and the capacity retention ratio reaches 82% with a columbic efficiency beyond 99%. The overpotential of P-SPE based symmetric battery is 0.08 V, and there is no apparent magnifying even after 130 h cycling. This new design provides a new avenue for exploitation of advanced SPEs for the next-generation batteries.

Fiber diameters and parallel patterns:proliferation and osteogenesis of stem cells

Due to the innate extracellular matrix mimicking features,fibrous materials exhibited great application potential in biomedicine.In developing excellent fibrous biomaterial,it is essential to reveal the corresponding inherent fiber features’effects on cell behaviors.Due to the inevitable‘interference’cell adhesions to the background or between adjacent fibers,it is difficult to precisely reveal the inherent fiber diameter effect on cell behaviors by using a traditional fiber mat.A single-layer and parallel-arranged polycaprolactone fiber pattern platform with an excellent non-fouling background is designed and constructed herein.In this unique material platform,the‘interference’cell adhesions through interspace between fibers to the environment could be effectively ruled out by the non-fouling background.The‘interference’cell adhesions between adjacent fibers could also be excluded from the sparsely arranged(SA)fiber patterns.The influence of fiber diameter on stem cell behaviors is precisely and comprehensively investigated based on eliminating the undesired‘interference’cell adhesions in a controllable way.On the SA fiber patterns,small diameter fiber(SA-D1,D1 means 1μm in diameter)may seriously restrict cell proliferation and osteogenesis when compared to the middle(SA-D8)and large(SA-D56)ones and SA-D8 shows the optimal osteogenesis enhancement effect.At the same time,the cells present similar proliferation ability and even the highest osteogenic ability on the densely arranged(DA)fiber patterns with small diameter fiber(DA-D1)when compared to the middle(DA-D8)and large(DA-D56)ones.The‘interference’cell adhesion between adjacent fibers under dense fiber arrangement may be the main reason for inducing these different cell behavior trends along with fiber diameters.Related results and comparisons have illustrated the effects of fiber diameter on stem cell behaviors more precisely and objectively,thus providing valuable reference and guidance for developing effective fibrous biomaterials.

Characteristics of Si-PIN nuclear radiation detectors stacked in series and parallel

The silicon-based diodes coated with a thin film of neutron reactive materials have been shown to produce excellent neutron detectors. We have fabricated the thin-film-coated single Si-PIN neutron detectors and stacked ones coupled in series and parallel in this work. The stacked detectors show the advantage of improving the detection efficiency of neutron detecting, which essentially attributes to the increase of the effective detection area. It is shown that the stacked detector in series has more superior performance than the parallel one. This work provides a feasible method to develop solid-state semiconductor neutron detectors with high neutron detection efficiency and high response speed.

An Explicit Solution for a Series and Parallel Queue with Retrial,Losses,and Bernoulli Schedule

This paper deals with the series and parallel queueing system in which there are two servers whose service time follow two exponential distributions.Each arriving customer either enters into the tandem service with probability or joins the service of the single server with complementary probability.We assume that the customers of arriving at the first server who find the first server is busy join an orbit and retry to enter the server after some time and of arriving at the second server who find the second server is busy are lost.For this model,we obtain the explicit expressions of the joint stationary distribution between the number of customers in the orbit and the states of the servers.

Parallel finite element computation of incompressible magnetohydrodynamics based on three iterations

Based on local algorithms,some parallel finite element(FE)iterative methods for stationary incompressible magnetohydrodynamics(MHD)are presented.These approaches are on account of two-grid skill include two major phases:find the FE solution by solving the nonlinear system on a globally coarse mesh to seize the low frequency component of the solution,and then locally solve linearized residual subproblems by one of three iterations(Stokes-type,Newton,and Oseen-type)on subdomains with fine grid in parallel to approximate the high frequency component.Optimal error estimates with regard to two mesh sizes and iterative steps of the proposed algorithms are given.Some numerical examples are implemented to verify the algorithm.

ON INCREASING THE PARALLELISM IN NUMERICAL ALGORITHMS

Parallel algorithms have been designed for the past 20 years initially by parallelising existing sequential algorithms for many different parallel architectures. More recently parallel strategies have been identified and utilized 'resulting in many new parallel algorithms. However the analysis of such algorithms reveals that further strategies can be applied to increase the parallelism. One of these, i.e., increasing the computational capacity in each processing node can reduce the congestion/communicgtion for shared memory/distributed memory multiprocessor systems and dramahcally improve the Performance of the algorithm. Two algorithms are identified and studied, i.e., the Cyclic reduction method for solving large tridiagonal linear systems in which the odd/even sequence is increased to a 'stride of 3' or more resulting in an improved algorithm. Similarly the Gaussian Elimination method for solving linear systems in which one element is eliminated at a time can be adapted to parallel form in which two elements are simultaneously eliminated resulting in the Parallel Implicit Elimination (P.I.E.) method. Numerical results are presented to support the analyses.

Modular Reciprocating HVDC Circuit Breaker with Current-limiting and Bi-directional Series-parallel Branch Switching Capability

The high-voltage direct current(HVDC)circuit breaker is becoming popular with the rapid development of the flexible HVDC grid for efficient DC fault ride-through purposes.This paper proposes a novel module for reciprocating HVDC circuit breaker topology,whose branch connections are able to switch between series and parallel modes to limit the rising rate and interrupt the DC fault currents.Diode-bridge submodules(DBSMs)are used to compose the main branch for current interruption.Besides fault clearance,the proposed topology has the advantageous function of DC fault current limiting by employing DBSMs with bi-directional conduction capability.The topology can easily switch among branch connection modes through the assembled trans-valves,and their resistance and reactance are very small in the normal state when branches are in parallel and the values become promptly large in the transient state when the branches are series connected.With the modular design,it is easy to change the number of branches or sub-modules and the types of sub-modules to adapt to more specific needs.A 6-terminal modular multi-level converter(MMC)based HVDC grid is established in PSCAD/EMTDC,and various simulation scenarios are carried out to validate the proposed topology.

Neurodynamics analysis of brain information transmission

This paper proposes a model of neural networks consisting of populations of perceptive neurons, inter-neurons, and motor neurons according to the theory of stochastic phase resetting dynamics. According to this model, the dynamical characteristics of neural networks are studied in three coupling cases, namely, series and parallel coupling, series coupling, and unilateral coupling. The results show that the indentified structure of neural networks enables the basic characteristics of neural information processing to be described in terms of the actions of both the optional motor and the reflected motor. The excitation of local neural networks is caused by the action of the optional motor. In particular, the excitation of the neural population caused by the action of the optional motor in the motor cortex is larger than that caused by the action of the reflected motor. This phenomenon indicates that there are more neurons participating in the neural information processing and the excited synchronization motion under the action of the optional motor.

Design of a Hardware-Implemented Phase Calculating System for Feedback Control in the LHCD Experiments on EAST

A fully hardware-implemented phase calculating system for the feedback control in the lower-hybrid current drive （LHCD） experiments is presented in this paper. By taking advantages of field programmable gate array （FPGA） chips with embedded digital signal processing （DSP） cores and the Matlab-aided design method, the phase calculating algorithm with a square root operation and parallel process are efficiently implemented in a single FPGA chip to complete the calculation of phase differences fast and accurately in the lower-hybrid wave （LHW） system on EAST.

Grid-based internet worm behavior simulator

The traditional network simulator has function and performance limitation when simulating Internet worms,so we designed the grid-based Internet worm behavior simulator (IWBS Grid).IWBS Grid makes use of the real Internet topology,link and routing information,and simulates the worm behavior at the packet event-driven level;and proposes a high-performance Internet worms behavior simulation platform by right of the grid computing capability,resource and task management,and so on.The experimental results show that IWBS grid surpasses the traditional simulator in simulating capability,and the technology to track the worm propagation in packet level can propose the valuable information for the further study on worms.

Adaptive Distributed Admission Control in Differentiated Services Domains

In this paper we propose a scalable admission control scheme for the QoS sensitivity traffic in DiffServ domains. In our scheme, the ingress touters perform admissibility test in a fully distributed and parallel fashion for requests based on our resource per-assigning mechanism. Then, we introduce a novel two phase token passing mechanism to adaptively optimize resource per-assigning among contending edge touters in proportion to their traffic. In addition, we adopt a measurement based admission decision-making criterion to gain the benefit of high utilization of statistical multiplexing. Our simulation results indicate that even under very high request load it is possible to perform admission control and resource allocation in parallel without suffering in terms of response time, packet loss rate, or utilization.

CONVERGENCE ANALYSIS OF SOME FINITE ELEMENT PARALLEL ALGORITHMS FOR THE STATIONARY INCOMPRESSIBLE MHD EQUATIONS

By combination of iteration methods with the partition of unity method(PUM),some finite element parallel algorithms for the stationary incompressible magnetohydrodynamics(MHD)with different physical parameters are presented and analyzed.These algorithms are highly efficient.At first,a global solution is obtained on a coarse grid for all approaches by one of the iteration methods.By parallelized residual schemes,local corrected solutions are calculated on finer meshes with overlapping sub-domains.The subdomains can be achieved flexibly by a class of PUM.The proposed algorithm is proved to be uniformly stable and convergent.Finally,one numerical example is presented to confirm the theoretical findings.

Hybrid robust fault detection and isolation of satellite reaction wheel actuators

In this paper,a combined robust fault detection and isolation scheme is studied for satellite system subject to actuator faults,external disturbances,and parametric uncertainties.The proposed methodology incorporates a residual generation module,including a bank of filters,into an intelligent residual evaluation module.First,residual filters are designed based on an improved nonlinear differential algebraic approach so that they are not affected by external disturbances.The residual evaluation module is developed based on the suggested series and parallel forms.Further,a new ensemble classification scheme defined as blended learning integrates heterogeneous classifiers to enhance the performance.A wide range of simulations is carried out in a high-fidelity satellite simulator subject to the constant and time-varying actuator faults in the presence of disturbances,manoeuvres,uncertainties,and noises.The obtained results demonstrate the effectiveness of the proposed robust fault detection and isolation method compared to the traditional nonlinear differential algebraic approach.

A Survey of Data Partitioning and Sampling Methods to Support Big Data Analysis

Computer clusters with the shared-nothing architecture are the major computing platforms for big data processing and analysis.In cluster computing,data partitioning and sampling are two fundamental strategies to speed up the computation of big data and increase scalability.In this paper,we present a comprehensive survey of the methods and techniques of data partitioning and sampling with respect to big data processing and analysis.We start with an overview of the mainstream big data frameworks on Hadoop clusters.The basic methods of data partitioning are then discussed including three classical horizontal partitioning schemes:range,hash,and random partitioning.Data partitioning on Hadoop clusters is also discussed with a summary of new strategies for big data partitioning,including the new Random Sample Partition(RSP)distributed model.The classical methods of data sampling are then investigated,including simple random sampling,stratified sampling,and reservoir sampling.Two common methods of big data sampling on computing clusters are also discussed:record-level sampling and blocklevel sampling.Record-level sampling is not as efficient as block-level sampling on big distributed data.On the other hand,block-level sampling on data blocks generated with the classical data partitioning methods does not necessarily produce good representative samples for approximate computing of big data.In this survey,we also summarize the prevailing strategies and related work on sampling-based approximation on Hadoop clusters.We believe that data partitioning and sampling should be considered together to build approximate cluster computing frameworks that are reliable in both the computational and statistical respects.

CHARACTERISTIC ALTERNATING-DIRECTION FINITE ELEMENT METHODS FOR NONRECTANGULAR REGIONS FOR COUPLED SYSTEM OF DYNAMICS OF FLUIDS IN POROUS MEDIA AND ITS ANALYSIS

For coupled system of multilayer dynamics of fluids in porous media, thecharacteristic alternating-direction finite element methods for nonrectangular regions applicable toparallel arithmetic are put forward and two-dimensional and three-dimensional schemes are used toform a complete set. Some techniques, such as calculus of variations, isoparametric transformation,patch approximation, operator-splitting, characteristic method, negative norm estimate, energymethod, the theory of prior estimates and techniques are used. For the nonrectangular regions case,optimal order estimates in L^2 norm are derived for the error in the approximation solution. Thusthe well-known theoretical problem has been thoroughly and completely solved. These methods havebeen successfully used in multilayer oil resources migration-accumulation numerical simulation.

A Non-Blocking Locking Method and Performance Evaluation on Network of Workstations

network of workstation (NOW) can act as a single and scalable powerful computer by building a parallel and distributed computing platformon top of it. WAKASHI is such a platform system that supports persistent objectmanagement and makes full use of resources of NOW for high performance transaction processing. One of the main difficulties to overcome is the bottleneck causedby concurrency control mechanism. Therefore, a non-blocking locking method isdesigned, by adopting several novel techniques to make it outperform the other typical locking methods such as 2PL: 1) an SDG (Semantic Dependency Graph) basednon-blocking locking protocol for fast transaction scheduling; 2) a massively virtualmemory based backup-page undo algorithm for fast restart; and 3) a multi-processorand multi-thread based transaction manager for fast execution. The new mechanismshave been implemented in WAKASHI and the performance comparison experimentswith 2PL and DWDL have been done. The results show that the new method canoutperform 2PL and DWDL under certain conditions. This is meaningful for Choosing effective concurrency control mechanisms for improving transaction- processingperformance in NOW environments.